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Participatory Disaster Recovery Simulation Modeling for Community Resilience Planning

Authors :
Scott B. Miles
Source :
International Journal of Disaster Risk Science, Vol 9, Iss 4, Pp 519-529 (2018)
Publication Year :
2018
Publisher :
SpringerOpen, 2018.

Abstract

Abstract A major challenge in enhancing the resilience of communities stems from current approaches used to identify needs and strategies that build the capacity of jurisdictions to mitigate loss and improve recovery. A new generation of resilience-based planning processes has emerged in the last several years that integrate goals of community well-being and identity into recovery-based performance measurement frameworks. Specific tools and refined guidance are needed to facilitate evidence-based development of recovery estimates. This article presents the participatory modeling process, a planning system designed to develop recovery-based resilience measurement frameworks for community resilience planning initiatives. Stakeholder engagement is infused throughout the participatory modeling process by integrating disaster recovery simulation modeling into community resilience planning. Within the process, participants get a unique opportunity to work together to deliberate on community concerns through facilitated participatory modeling. The participatory modeling platform combines the DESaster recovery simulation model and visual analytics interfaces. DESaster is an open source Python Library for creating discrete event simulations of disaster recovery. The simulation model was developed using a human-centered design approach whose goal is to be open, modular, and extensible. The process presented in this article is the first participatory modeling approach for analyzing recovery to aid creation of community resilience measurement frameworks.

Details

Language :
English
ISSN :
20950055 and 21926395
Volume :
9
Issue :
4
Database :
Directory of Open Access Journals
Journal :
International Journal of Disaster Risk Science
Publication Type :
Academic Journal
Accession number :
edsdoj.7f33b92e412e47ff8d452e4351313025
Document Type :
article
Full Text :
https://doi.org/10.1007/s13753-018-0202-9